Sr. Data Engineer at is a software product company that provides · Hyderabad · 6 - 15 years · ₹11L - ₹15L / yr · Posted 2 Sep 2023

Sr. Data Engineer
at is a software product company that provides
5+ years of experience designing, developing, validating, and automating ETL processes 3+ years of experience traditional ETL tools such as Visual Studio, SQL Server Management Studio, SSIS, SSAS and SSRS 2+ years of experience with cloud technologies and platforms, such as: Kubernetes, Spark, Kafka, Azure Data Factory, Snowflake, ML Flow, Databricks, Airflow or similar Must have experience with designing and implementing data access layers Must be an expert with SQL/T-SQL and Python Must have experience in Kafka Define and implement data models with various database technologies like MongoDB, CosmosDB, Neo4j, MariaDB and SQL Serve Ingest and publish data from sources and to destinations via an API Exposure to ETL/ELT with using Kafka or Azure Event Hubs with Spark or Databricks is a plus Exposure to healthcare technologies and integrations for FHIR API, HL7 or other HIE protocols is a plus
Skills Required :
Designing, Developing, ETL, Visual Studio, Python, Spark, Kubernetes, Kafka, Azure Data Factory, SQL Server, Airflow, Databricks, T-SQL, MongoDB, CosmosDB, Snowflake, SSIS, SSAS, SSRS, FHIR API, HL7, HIE Protocols

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Urgent Hiring – Senior Data Engineer
We are hiring for a Senior Data Engineer for a reputed product-based company in Pune.
Location: Pune – Magarpatta / Baner
Experience: 7–10 Years
Work Mode: 5 Days WFO
Notice Period: Immediate to 30 Days preferred
What We're Looking For
- 7+ years of hands-on experience in Data Engineering
- 5+ years of experience in Python
- 4+ years of experience in Snowflake
- 5+ years of experience in SQL
- 5+ years of experience with ADF / Fivetran / Matillion or equivalent Data Integration tools
- Hands-on experience with AWS / Azure
- Experience with Airflow or equivalent orchestration tools
- Strong experience in ETL/ELT and Data Pipelines
- Experience with APIs, JSON, XML and Webhooks
- Knowledge of CI/CD, Git and automated testing
- Exposure to dbt or similar transformation tools
- Experience in data pipeline monitoring, troubleshooting and performance optimization
Key Responsibilities
- Design, develop and maintain scalable ETL/ELT data pipelines
- Build batch, real-time and on-demand data processing workflows
- Integrate data from cloud and on-premise sources
- Ensure data quality, reliability, performance and SLA adherence
- Work closely with Data Scientists, Analysts, DevOps and Business teams
- Implement data engineering best practices, CI/CD and automated testing
- Troubleshoot pipeline issues and perform root cause analysis
- Optimize data pipelines and SQL queries for performance and cost efficiency
Why Join?
- Opportunity to work with a reputed product-based organization
- Work on modern data engineering and cloud technologies
- Exposure to large-scale data platforms and business-critical data solutions
- Collaborative and technically strong environment
Interested candidates can share their updated CV for immediate consideration.
Data Engineer – Microsoft Fabric
Location: Pune, India
Work Mode: Hybrid
Experience: 6+ Years
Employment Type: Full-time contactor
Compensation: As per market standards, commensurate with experience and expertise
Shift Timings: 2:00 PM – 11:00 PM IST
Notice Period: 0 – 15 days
About the Role
Jade Business Services (JBS) is seeking a Data Engineer – Microsoft Fabric to join our Pune team and work on enterprise-scale data transformation and analytics initiatives.
We are looking for a hands-on Data Engineer with strong experience in Microsoft Fabric, SQL, Python/PySpark and modern data engineering practices. The candidate will be responsible for building scalable data pipelines, implementing Lakehouse and Warehouse solutions, developing data models and supporting governed, reliable and AI-ready data platforms.
The ideal candidate should be comfortable working with architects, engineering teams and client stakeholders to translate business requirements into scalable and production-ready data solutions.
Roles and Responsibilities
- Design and develop data solutions using Microsoft Fabric, including OneLake, Lakehouse, Warehouse and Data Factory pipelines.
- Build and maintain scalable ETL/ELT pipelines for batch and incremental data processing.
- Develop data ingestion and transformation pipelines using Fabric Data Factory, SQL, Python and/or PySpark.
- Implement Medallion Architecture using Bronze, Silver and Gold layers.
- Work with Lakehouse and Fabric Warehouse for enterprise data processing and analytics.
- Develop and maintain data models, tables, views and optimized SQL queries.
- Build and support semantic models for Power BI and analytical workloads.
- Implement data quality, validation, monitoring and error-handling mechanisms.
- Work with metadata, lineage and governance requirements using Microsoft Purview.
- Implement data security, access controls and role-based permissions across data platforms.
- Support Data Product and domain-oriented data architecture principles.
- Follow DataOps practices including CI/CD, deployment, monitoring and production support.
- Troubleshoot pipeline failures, performance issues and data quality problems.
- Optimize data pipelines, queries and storage for performance and cost efficiency.
- Work closely with Data Architects and business stakeholders to understand requirements and implement technical solutions.
- Participate in technical design discussions, code reviews and architecture reviews.
- Maintain technical documentation, data flow diagrams and pipeline documentation.
- Support production deployments, incident resolution and SLA-driven data platform operations.
- Identify opportunities for automation and AI-assisted improvements across data engineering processes.
Qualifications and Skills
- 6+ years of experience in Data Engineering, Data Integration or Data Platform development.
- Strong hands-on experience with Microsoft Fabric.
- Experience with:
- Microsoft Fabric Lakehouse
- Fabric Warehouse
- OneLake
- Fabric Data Factory / Pipelines
- Semantic Models
- Strong understanding of Lakehouse and Medallion Architecture.
- Strong SQL development and query optimization skills.
- Hands-on experience with Python and/or PySpark.
- Experience developing enterprise ETL/ELT and data integration pipelines.
- Experience with batch and incremental data processing.
- Understanding of data modelling concepts including dimensional modelling.
- Knowledge of data quality, metadata, lineage and data governance.
- Working knowledge of Microsoft Purview.
- Understanding of Data Mesh and Data Product concepts.
- Experience with CI/CD, version control, monitoring and DataOps practices.
- Understanding of cloud security, access controls and data privacy.
- Good troubleshooting and problem-solving skills.
- Strong communication skills and ability to work with distributed and client-facing teams.
Preferred Skills
- Microsoft Fabric or Azure Data certifications.
- Experience migrating workloads from Azure Synapse, SQL Server, Databricks or other data platforms to Microsoft Fabric.
- Experience implementing Medallion Architecture on Microsoft Fabric.
- Experience with Power BI and semantic modelling.
- Exposure to AI/ML, Generative AI or Agentic AI use cases on enterprise data platforms.
- Experience working with Data Products or domain-oriented data solutions.
- Experience in Energy & Utilities, Healthcare, Financial Services or Insurance.
- Experience working with US or international enterprise clients.
What We Expect
The ideal candidate should be hands-on first and capable of independently building, troubleshooting and optimizing Fabric data solutions. You should be able to explain the technical decisions behind your implementation and work effectively with architects and engineering teams to deliver production-ready solutions.
Position: Backup Data ETL Developer
Experience: 6–9 Years
Location: Mumbai
Employment Type: Full-time
Job Description:
We are looking for a Backup Data ETL Developer with 6–9 years of experience in designing, developing, and supporting data extraction, transformation, and loading (ETL) processes.
The candidate should have strong hands-on experience with Hadoop, Spark, Informatica, and Snowflake, along with expertise in large-scale data processing and data integration technologies.
Key Skills:
Hadoop
Spark
Informatica
Snowflake
ETL Development
Data Integration
Data Transformation
Large-Scale Data Processing
ETL Workflows and Data Pipelines
Troubleshooting and Problem-Solving
Strong analytical and collaboration skills
Job Summary
Role Overview
We are looking for an experienced Data Engineer with strong expertise in Python, ETL, Advanced SQL, CI/CD, DevOps, and Data Analytics. The ideal candidate should have hands-on experience designing and developing scalable data pipelines, transforming large datasets, and supporting data-driven applications.
Experience with Google Cloud Platform (GCP) will be an added advantage.
Key Responsibilities
- Design, develop, and maintain scalable ETL/ELT data pipelines using Python and SQL.
- Develop complex and optimized SQL queries, stored procedures, and data transformations.
- Build and maintain reliable data integration workflows across multiple data sources.
- Perform data cleansing, validation, transformation, and quality checks.
- Analyze data and provide insights to support business and technical requirements.
- Implement and maintain CI/CD pipelines for data engineering applications.
- Work with DevOps practices and tools to automate deployments, monitoring, and infrastructure processes.
- Troubleshoot data pipeline failures, performance issues, and production incidents.
- Optimize data processing workflows for performance, scalability, and reliability.
- Collaborate with Data Analysts, Data Scientists, Developers, and other stakeholders.
- Follow best practices for version control, testing, documentation, and deployment.
- Contribute to cloud-based data engineering initiatives, preferably on GCP.
Required Skills
- 5–7 years of hands-on experience in Data Engineering.
- Strong programming skills in Python.
- Strong expertise in Advanced SQL and database concepts.
- Hands-on experience with ETL/ELT processes and data pipelines.
- Good understanding of Data Warehousing and Data Modeling concepts.
- Experience with CI/CD practices and tools.
- Strong understanding of DevOps principles, automation, and deployment processes.
- Strong data analytics and problem-solving skills.
- Experience working with large datasets and performance optimization.
- Good understanding of Git/version control and software development best practices.
Good to Have
- Hands-on experience with Google Cloud Platform (GCP).
- Exposure to GCP data services such as BigQuery, Cloud Storage, Dataflow, Composer, or Pub/Sub.
- Experience with containerization/orchestration technologies such as Docker/Kubernetes.
- Experience with workflow orchestration tools such as Airflow.
- Knowledge of cloud-based data architecture and distributed data processing.
Preferred Candidate Profile
- Strong analytical and problem-solving abilities.
- Good communication and stakeholder management skills.
- Ability to work independently as well as in a collaborative team environment.
- Strong ownership of data pipelines and production systems.
- Candidates who can join at short notice are preferred.
Mandatory Skills
Data Engineer, Python , ETL, GCP, Advanced SQL, Strong Data Analytics skills, CICD, Devops
Job Summary
We are looking for a skilled and experienced Data Engineer to join our growing data team. The ideal candidate will have strong expertise in Python, PySpark, Data Modeling, and Power BI, with hands-on experience in designing, developing, and optimizing scalable data solutions. The role requires working closely with business stakeholders, data architects, and analytics teams to build robust data pipelines and semantic models that enable data-driven decision-making.
Technical Skills
- Strong hands-on experience in Python and PySpark development.
- Expertise in building and optimizing Data Engineering solutions and ETL pipelines.
- Strong understanding of Data Modeling concepts (Star Schema, Snowflake Schema, Dimensional Modeling).
- Experience with Power BI Data Modeling and Semantic Layer development.
- Proficiency in DAX (Data Analysis Expressions).
- Experience designing and managing Semantic Models in Power BI.
- Strong SQL skills and experience working with large datasets.
- Knowledge of data warehousing concepts and best practices.
Preferred Skills
- Experience with cloud platforms such as Azure, AWS, or GCP.
- Exposure to modern data platforms like Databricks.
- Understanding of data governance and data quality frameworks.
Location: Bangalore Experience: 5 to 7 years Employment type: Full-time, permanent Work Hours: General Shift (10.00 AM to 7.00 PM) website: www.amazech.com Qualifications: Minimum B.E./B.Tech, or higher in Computer Science, Information Technology, Data Engineering, or a related field, with a good academic background. Key Responsibilities: • Design, develop, and maintain end-to-end data pipelines. • Build and optimize ETL/ELT processes for large-scale data processing. • Implement Azure-based data solutions ensuring scalability and performance. • Collaborate with stakeholders to understand business data requirements. • Perform performance tuning and optimization across data platforms. • Support production environments, conduct root cause analysis, and resolve data-related issues. • Maintain comprehensive technical documentation and structured knowledge transfer documents. • Work effectively within Agile/Scrum frameworks and contribute to sprint planning and delivery. • Ensure secure and compliant data handling using Azure best practices. Required Skills & Experience • End-to-end ETL/ELT pipeline development, integration, and performance optimization • Azure Synapse, Azure Logic Apps, Azure SQL, and Azure Databricks, with a strong focus on performance tuning • Microsoft Azure services, including Storage Accounts, Key Vault, and Cognitive Services • Advanced proficiency in Python development and modern productivity tools such as GitHub Copilot and Cursor • Strong documentation discipline, including technical design documentation, and structured knowledge transfer documents • Experience operating within Agile/Scrum frameworks, including production support, root cause analysis, and effective stakeholder collaboration
Data Engineer Short Hiring Post
🚨 Hiring: Data Engineer
🔹 Experience: 5–9 Years
🔹 Location: Bangalore / Hyderabad
🔹 Skills: PySpark, Python, SQL, ETL, CI/CD, Data Modeling
🔹 Process: L1 Virtual → L2 F2F Karat Test
🔹 F2F: Bangalore / Hyderabad Location
🔹 Positions: Immediate requirement
⚠️ Note: Candidates must be available for F2F Karat immediately after L1.
#Hiring #DataEngineer #PySpark #Python #SQL #BangaloreJobs #HyderabadJobs #Mphasis #ImmediateJoiners
We are looking for a dynamic Data Engineer to join our team of technology enthusiasts. You will leverage data to drive strategic decision-making and pioneering solutions, working with complex datasets, collaborating closely with stakeholders, and transforming data into actionable insights to drive innovation.
Qualifications and Skills:
- Minimum 5 years of experience as a Data Engineer
- Hands-on experience with Azure cloud-based data solutions
- Expertise in database design and management, including SQL databases such as SQL Server
- Proficient in ETL (Extract, Transform, Load) design for data integration and processing
- Strong knowledge of data modeling principles and techniques
- Ability to analyze and translate data into actionable insights, reports, and visualizations
- Proficiency in Power BI for reporting and data visualization
Desirable Skills:
- Experience with Power BI Report Builder / Reporting Services
- Knowledge of statistical analysis or Data Science
- Experience within the UK Insurance industry is a plus
- Python or R coding skills
Responsibilities:
- Implement efficient data exchange between internal and external systems to increase efficiency and reduce re-keying and translation errors
- Support the Broking business by developing high-quality information resources, ensuring data availability and accessibility for decision-making
- Engineer data inputs and outputs from core applications and semi-structured remote service data through data syncs between data lake, ODS (SQL database), and leveraging Fabric and ADF
- Perform data engineering tasks including ingestion, cleansing, and collation from a wide range of internal and external sources
- Implement different methods of streaming data and create reconciliations for datasets
- Build analytical models to support reporting and analytics
- Collaborate with an agile delivery team to work on the backlog of specified work
Location – Hyderabad (Hybrid)
Work Experience – 5 to 7 years
CTC – upto 20 LPA
Roles & Responsibilities:
· We are looking for a Senior Data Engineering who will be majorly responsible for designing, building and maintaining ETL/ ELT pipelines.
· Integration of data from multiple sources or vendors to provide the holistic insights from data.
· You are expected to build and manage Data warehouse solutions, designing data models, creating ETL processes, implementing data quality mechanisms etc.
· Performs EDA (exploratory data analysis) required to troubleshoot data related issues and assist in the resolution of data issues.
· Should have experience in client interaction.
· Experience in mentoring juniors and providing required guidance.
Required Technical Skills
· Extensive hands on experience in Python, Pyspark, SQL, Dataiku.
· Strong experience in Data Warehouse, ETL, Data Modelling, building ETL Pipelines, Snowflake database.
· Working knowledge in Databricks, Redshift, ADF etc.
· Hands-on experience in cloud services like Azure, AWS- S3, Glue, Lambda, CloudWatch, Athena.
· Sound knowledge in end-to-end Data management, Data ops, quality and data governance.
· Familiar with SFDC, Waterfall/ Agile methodology.
· Strong domain knowledge in Pharma domain/ life sciences commercial data operations.
Qualifications
· Bachelor’s or master’s Engineering/ MCA or equivalent degree.
· 5-7 years of relevant industry experience as Data Engineer.
· Experience working on Pharma syndicated data such as IQVIA, Veeva, Symphony; Claims, CRM, Sales etc.
· High motivation, good work ethic, maturity, self-organized and personal initiative.
· Ability to work collaboratively and providing the support to the team.
· Excellent written and verbal communication skills.
· Strong analytical and problem-solving skills.
Description
We are looking for Senior Data Engineers to join our Data Platform team and build scalable, high-performance data platforms that power data processing, analytics, and downstream applications.
The ideal candidate will have strong experience in distributed data processing, ETL pipelines, and Big Data technologies, with hands-on expertise in Apache Spark and Python Scala.
You will be responsible for designing, developing, and optimizing large-scale data pipelines while collaborating closely with cross-functional engineering teams to build reliable, production-grade data solutions.
Key Responsibilities
- Design, develop, and maintain scalable ETL and data processing pipelines for large-scale datasets.
- Build and optimize distributed data applications using Apache Spark and Python Scala.
- Develop reliable, high-performance data pipelines for batch and streaming workloads.
- Design and manage data workflows using Apache Airflow.
- Build and operate data workloads on AWS, with strong usage of Amazon S3 for large-scale data storage.
- Work with large datasets to ensure data quality, consistency, reliability, and performance.
- Collaborate with engineering, product, analytics, and other platform teams to deliver robust data solutions.
- Optimize data workflows for scalability, reliability, performance, and cost efficiency.
- Troubleshoot production issues, identify bottlenecks, and continuously improve platform performance.
Requirements
Candidates who demonstrate:
- 5+ years of experience in Data Engineering, Big Data Engineering, or a similar role.
- Strong hands-on experience with Apache Spark and Scala.
- Experience designing, building, and maintaining large-scale ETL pipelines.
- Strong hands-on experience with AWS, particularly Amazon S3.
- Hands-on experience with Apache Airflow for workflow orchestration and scheduling.
- Strong SQL skills and a solid understanding of distributed data processing concepts.
- Experience working with batch and/or streaming data pipelines.
- Excellent debugging, problem-solving, and performance optimization skills.
- Strong communication and collaboration skills.
Good to Have
- Experience with Databricks and the broader Databricks data platform.
- Familiarity with streaming technologies such as Apache Kafka.
- Experience working on large-scale data platforms handling high-volume data workloads.
- Exposure to additional AWS data services and cloud-native data architectures.














